{"title":"无代码平台的时间序列预测","authors":"Youcef Guichi, Erika Baksáné Varga","doi":"10.32968/psaie.2022.3.7","DOIUrl":null,"url":null,"abstract":"Machine learning platforms that provide no-code capabilities allow for users to use machine learning without advanced domain knowledge or training. These tools enable those having no formal expertise in software development to create machine learning applications. Our analysis of existing no-code ML platforms reveals that most of them offer core ML, but not deep learning network models and can not be accessed for free. Therefore we have created a web-based application that allows researchers to experiment with machine learning solutions concerning time series prediction without the need for coding. This paper presents a case study demonstrating the operation of the platform.","PeriodicalId":117509,"journal":{"name":"Production Systems and Information Engineering","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"No-code platform for time series prediction\",\"authors\":\"Youcef Guichi, Erika Baksáné Varga\",\"doi\":\"10.32968/psaie.2022.3.7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Machine learning platforms that provide no-code capabilities allow for users to use machine learning without advanced domain knowledge or training. These tools enable those having no formal expertise in software development to create machine learning applications. Our analysis of existing no-code ML platforms reveals that most of them offer core ML, but not deep learning network models and can not be accessed for free. Therefore we have created a web-based application that allows researchers to experiment with machine learning solutions concerning time series prediction without the need for coding. This paper presents a case study demonstrating the operation of the platform.\",\"PeriodicalId\":117509,\"journal\":{\"name\":\"Production Systems and Information Engineering\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Production Systems and Information Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32968/psaie.2022.3.7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Production Systems and Information Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32968/psaie.2022.3.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine learning platforms that provide no-code capabilities allow for users to use machine learning without advanced domain knowledge or training. These tools enable those having no formal expertise in software development to create machine learning applications. Our analysis of existing no-code ML platforms reveals that most of them offer core ML, but not deep learning network models and can not be accessed for free. Therefore we have created a web-based application that allows researchers to experiment with machine learning solutions concerning time series prediction without the need for coding. This paper presents a case study demonstrating the operation of the platform.